Triple

T17517170
Position Surface form Disambiguated ID Type / Status
Subject Tensilica Xtensa LX6 E426597 entity
Predicate usedIn P98 FINISHED
Object Espressif ESP32-S0WD NE NERFINISHED

How this triple was built (3 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Espressif ESP32-S0WD | Statement: [Tensilica Xtensa LX6, usedIn, Espressif ESP32-S0WD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Espressif ESP32-S0WD
Context triple: [Tensilica Xtensa LX6, usedIn, Espressif ESP32-S0WD]
  • A. ESP32-DevKitC
    ESP32-DevKitC is a compact, official Espressif development board designed to prototype and evaluate ESP32 Wi‑Fi and Bluetooth microcontroller applications.
  • B. ESP32 microcontrollers
    ESP32 microcontrollers are low-cost, low-power Wi-Fi and Bluetooth-enabled system-on-chips from Espressif, widely used for IoT, embedded, and hobbyist electronics projects.
  • C. Espressif Systems
    Espressif Systems is a Chinese semiconductor company best known for designing low-cost, Wi‑Fi and Bluetooth-enabled microcontroller chips widely used in IoT and embedded applications.
  • D. Raspberry Pi Pico
    Raspberry Pi Pico is a low-cost, microcontroller-based development board from the Raspberry Pi Foundation built around the RP2040 chip for embedded and hobbyist projects.
  • E. Silicon Labs EFM32 microcontrollers
    Silicon Labs EFM32 microcontrollers are ultra-low-power 32-bit MCUs designed for energy-efficient embedded applications such as IoT, wearables, and battery-powered devices.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Espressif ESP32-S0WD
Target entity description: The Espressif ESP32-S0WD is a low-power, dual-core Wi-Fi and Bluetooth microcontroller SoC widely used in IoT and embedded applications.
  • A. ESP32-DevKitC
    ESP32-DevKitC is a compact, official Espressif development board designed to prototype and evaluate ESP32 Wi‑Fi and Bluetooth microcontroller applications.
  • B. ESP32 microcontrollers chosen
    ESP32 microcontrollers are low-cost, low-power Wi-Fi and Bluetooth-enabled system-on-chips from Espressif, widely used for IoT, embedded, and hobbyist electronics projects.
  • C. Espressif Systems
    Espressif Systems is a Chinese semiconductor company best known for designing low-cost, Wi‑Fi and Bluetooth-enabled microcontroller chips widely used in IoT and embedded applications.
  • D. Raspberry Pi Pico
    Raspberry Pi Pico is a low-cost, microcontroller-based development board from the Raspberry Pi Foundation built around the RP2040 chip for embedded and hobbyist projects.
  • E. Silicon Labs EFM32 microcontrollers
    Silicon Labs EFM32 microcontrollers are ultra-low-power 32-bit MCUs designed for energy-efficient embedded applications such as IoT, wearables, and battery-powered devices.
  • F. None of above.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452615a8481909974e9855ea7a8e4 completed April 19, 2026, 3:56 a.m.
Created at: April 10, 2026, 5:49 a.m.